Unmanned ground vehicles (UGVs) include remote-driven or self-driven land vehicles that can carry cameras, sensors, communications equipment, or other payloads. Self-driven or “autonomous” UGVs are essentially robotic platforms that are capable of operating outdoors and over a wide variety of terrain with little or no operator input. To perform optimally, autonomous vehicles should be capable of detecting obstacles in different types of terrain to identify traversable paths. Conventional implementations of autonomous vehicles can include laser detection and ranging (LADAR) sensors that are used to measure the range to each point within a scan area that sweeps across a horizontal line. Other conventional implementations either flood illuminate an entire scene with a single pulse or scan a laser line using rotating mirrors or similar rotating structure. Further, on-board global positioning system (GPS) and inertial navigation system (INS) sensors can provide geo-location information and information that indicates vehicle dynamics (e.g., position and altitude of the vehicle, as well as the velocity and angular velocity of the vehicle). Together, these systems can map traversable paths for the autonomous vehicle.
In spite of advances in LADAR, GPS, and INS, difficulties persist in object detection and avoidance. One conventional approach is detailed in U.S. Patent Application Publication 2010/0030473 to Au, which describes augmentation of autonomous guidance systems to implement scanning and stored range scans in variable sized buffers and is incorporated herein by reference in its entirety. As described, the scan information can be translated into an estimated ground plane using information from the GPS and INS systems. The estimated ground plane is used to classify traversable areas, non-traversable areas, and obstacle areas for navigation.